Embedded Files
PCB Version 2
PCB Version 2
The second iteration of the PCB includes header mounting holes for the Adafruit IMU and temperature sensor, MicroSD Breakout, and Feather ESP32 V2.
Power lines route to the 3V pin on all components to ensure a stable power supply is provided.
3D-Printed Electronics Mount
3D-Printed Electronics Mount
The final design of the instrumentation package consists of the PCBV2 mentioned above, but also a custom electronics mount designed to attach underneath the top plate of the drop vehicle. With built-in spacers, there's enough space for the pins of the female headers and the screw heads for drop vehicle attachment. The final design uses 64.59g of PLA matte filament.
PCB Version 1
PCB Version 1
The first iteration of the PCB includes header mounting holes for the Adafruit IMU, MicroSD Breakout, and ESP32-Devkit-V1.
The prototype has the power lines on the microcontroller swapped, making it incompatible with the MicroSD card breakout.
Proof of Concept Data Acquisition Package
Proof of Concept Data Acquisition Package
Headers were soldered onto the protoboard and jumper cables were used to connect them on the backside.
The Proof of Concept data acquisition package used a protoboard with headers, such that the boards could be removed if needed.
Sensor: Sun Founder MPU-9250 9-DoF IMU + Temperature Sensor
Board: ELEGOO ESP32 DevKit-V1
The sensor collected acceleration and rotation data while the ESP32 communicated data wirelessly via a web server.
The web server and data-saving script were written in C++. The data-processing script was written in MATLAB. All relevant files are on the team's GitHub page.
Risk Reduction Testing Data Acquisition Package
Risk Reduction Testing Data Acquisition Package
The first round of Risk Reduction testing used a mini-Breadboard.
Sensor: MPU6050 6-DOF IMU (Accelerometer + Gyroscope)
Board: UCSD Envision Custom ESP32S3-Dev Module
The sensor collected acceleration and rotation data while the ESP32 communicated data wirelessly via WiFi.
The data was logged using a Python script and filtered using a MATLAB script. All relevant scripts can be found on the team's GitHub repository.Â
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